Terraform is an infrastructure as code tool that lets you create, update, and version infrastructure by defining resources in configuration files. This allows for a repeated workflow for provisioning and managing your infrastructure.

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Setup guide

This page shows you how to use the Terraform Provider for Pinecone to manage Pinecone indexes and collections.

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Requirements

Ensure you have the following:

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Installation

The provider is registered in the official Terraform registry. This enables the provider to be auto-installed when you run terraform init. You can also download the latest binary for your target platform from the Releases tab.

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Enable the provider

To enable the provider in your Terraform configuration, set a PINECONE_API_KEY environment variable to your Pinecone API key and add the following to your Terraform configuration file:

terraform { 
  required_providers { 
    pinecone = { 
      source = "pinecone-io/pinecone" 
    } 
  } 
} 

provider "pinecone" {}

If your API key was set as an input variable, you can use that value in the declaration, for example:

provider "pinecone" {
  api_key = var.pinecone_api_key
}

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Resources

The Pinecone Terraform Provider supports index and collection resources.

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Indexes

The pinecone_index resource lets you create, delete, and update indexes.

// Create a dense index
resource "pinecone_index" "dense-index-tf" {
  name       = "tf-dense-index"
  dimension  = 1536
  metric     = "cosine"
  spec       = {
    serverless = {
      cloud  = "aws"
      region = "us-west-2"
    }
  }
  deletion_protection = "disabled"
  tags = {
    environment = "development"
  }
}

// Create a sparse index
resource "pinecone_index" "sparse-index-tf" {
  name      = "tf-sparse-index"
  dimension = 10
  metric = "dotproduct"
  vector_type = "sparse"
  spec = {
    serverless = {
      cloud  = "aws"
      region = "us-west-2"
    }
  }
  deletion_protection = "disabled"
  tags = {
    environment = "development"
  }
}

// Create a dense index with integrated embedding
resource "pinecone_index" "dense-index-integrated" {
  name      = "tf-dense-index-with-integrated-embedding"
  spec = {
    serverless = {
      cloud  = "aws"
      region = "us-west-2"
    }
  }
  embed = {
    model = "llama-text-embed-v2"
    field_map = {
      text = "chunk_text"
    }
  }
}

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Collections

The pinecone_collection resource lets you create, delete, and update collections for pod-based indexes.

resource "pinecone_index" "test" {
  name      = "tf-test-index"
  dimension = 10
  spec = {
    pod = {
      environment = "us-west4-gcp"
      pod_type    = "s1.x1"
    }
  }
}

resource "pinecone_collection" "example-collection" {
  name   = "tf-example-collection"
  source = pinecone_index.test.name

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Limitations

The Terraform Provider for Pinecone does not support the following resources:

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Additional resources